kfzteile24 Best and Worst Cities to Drive 2017

At kfzteile24, we believe every city should be great to drive in. We conducted a study to discover which are the best and worst cities for driving, with the aim of enriching the debate around modern mobility and encouraging cities to learn from each other’s positive urban engagements and legislation.

The study examined several factors; congestion levels, public transport options, average cost of parking, cost of fuel, average speeds, levels of air pollution, accidents and fatalities, road quality and the frequency/perception of road rage. Any traffic delays or congestion caused by temporary construction work was not taken into account for this study. Once all factors were researched for 100 cities, a final score was calculated for each.

“Cars are an important accessory of modern life, and the means by which many use to get from A to B. Yet poor urban planning or a lack of civil education can make driving the most stressful experience of somebody’s day.” commented Thomas Kloubert, CMO of kfzteile24. “We hope that this study will act as a catalyst for those cities in the negative end of the ranking to invest in safer, cleaner and more efficient roads, and consider how methods adopted by higher scoring cities can be utilised in their own locations.”

Best and Worst Cities to Drive

Congestion Level

Gasoline (USD/Liter)

Diesel (USD/Liter)

Public Transport Alternative (Score)

Cost of Parking (USD/hr)

Downtown - Airport Speed (miles/hr)

Air Pollution (Score)

Road Traffic Injuries (Score)

Road Quality (Score)

Road Rage (Score)

Rank

Global Results

#

City

Country

1

Düsseldorf

Germany

20%

1.52

1.31

8.88

1.74

21.20

5.55

7.03

9.23

8.96

1

2

Dubai

UAE

26%

0.48

0.51

3.81

4.54

31.70

8.00

9.13

8.24

8.65

2

3

Zurich

Switzerland

31%

1.42

1.49

9.59

3.65

25.50

7.00

8.78

9.80

9.86

3

4

Tokyo

Japan

26%

1.14

0.94

10.00

4.18

30.50

4.27

6.94

8.83

8.45

4

5

Basel

Switzerland

27%

1.42

1.49

9.01

2.55

17.50

7.64

10.00

9.80

9.91

5

6

Singapore

Singapore

38%

1.44

0.99

8.56

1.39

32.40

3.45

8.69

10.00

8.25

6

7

Dortmund

Germany

23%

1.49

1.26

7.39

1.74

19.90

5.18

7.03

9.23

9.01

7

8

Vienna

Austria

31%

1.26

1.16

9.75

3.94

28.00

5.09

5.81

9.60

9.87

8

9

Munich

Germany

30%

1.50

1.28

9.26

2.09

27.40

6.73

7.03

9.23

7.28

9

10

Calgary

Canada

20%

0.93

0.77

8.27

10.96

26.80

10.00

5.19

8.83

7.19

10

11

Bern

Switzerland

19%

1.42

1.49

8.65

2.78

12.40

6.45

10.00

9.80

9.78

11

12

Stuttgart

Germany

28%

1.50

1.27

8.06

2.09

24.90

5.73

7.03

9.23

8.18

12

13

Montreal

Canada

29%

0.93

0.77

9.01

7.04

23.00

8.82

5.19

8.83

8.81

13

14

Toronto

Canada

30%

0.93

0.77

8.69

7.83

25.60

9.18

5.19

8.83

8.38

14

15

Helsinki

Finland

31%

1.55

1.34

8.85

4.18

20.00

7.64

6.42

10.00

10.00

15

16

Seattle

United States

34%

0.70

0.67

8.27

10.61

36.10

9.82

3.10

8.43

9.37

16

17

Frankfurt

Germany

28%

1.51

1.27

7.64

3.13

20.50

4.73

7.03

9.23

8.78

17

18

Amsterdam

Netherlands

22%

1.67

1.30

6.36

5.45

18.80

6.09

8.51

9.03

9.51

18

19

Perth

Australia

27%

0.90

0.94

5.21

2.78

21.20

8.27

5.81

7.26

8.29

19

20

Essen

Germany

28%

1.48

1.26

5.46

2.61

20.00

5.91

7.03

9.23

8.83

20

21

Madrid

Spain

25%

1.29

1.17

3.97

2.90

24.30

7.91

8.17

8.83

6.15

21

22

Ottawa

Canada

28%

0.93

0.77

7.52

6.66

18.10

9.91

5.19

8.83

8.45

22

23

San Antonio

United States

20%

0.70

0.67

4.96

10.12

24.90

8.64

3.10

8.43

8.22

23

24

Geneva

Switzerland

29%

1.42

1.49

8.87

3.57

11.20

7.27

10.00

9.80

9.73

24

25

Hamburg

Germany

33%

1.49

1.25

8.42

1.74

12.50

6.82

7.03

9.23

9.26

25

26

Stockholm

Sweden

28%

1.57

1.53

5.88

9.05

36.20

5.00

9.65

8.24

9.33

26

27

Marseille

France

29%

1.46

1.31

4.06

2.67

29.90

4.09

6.42

10.00

8.45

27

28

Prague

Czech Republic

23%

1.20

1.16

7.35

4.41

16.80

4.55

8.43

8.43

7.17

28

29

Graz

Austria

29%

1.26

1.16

6.71

3.02

16.20

5.36

5.81

9.60

9.86

29

30

Rotterdam

Netherlands

19%

1.67

1.30

8.76

4.64

13.10

6.00

8.51

9.03

6.54

30

31

Berlin

Germany

29%

1.49

1.26

9.84

1.97

13.10

5.82

7.03

9.23

6.11

31

32

Barcelona

Spain

31%

1.29

1.17

6.71

3.94

20.00

5.64

8.17

8.83

7.19

32

33

Cologne

Germany

34%

1.51

1.27

6.94

2.09

20.60

5.45

7.03

9.23

7.03

33

34

Birmingham

UK

40%

1.51

1.52

8.43

4.54

27.30

9.55

9.13

8.24

6.44

34

35

Bremen

Germany

32%

1.51

1.27

8.22

2.67

11.20

7.09

7.03

9.23

8.81

35

36

Seoul

Korea

30%

1.27

1.09

9.33

5.36

29.30

2.82

4.15

8.63

6.85

36

37

Oslo

Norway

30%

1.83

1.70

8.09

6.15

44.10

6.36

8.08

4.33

9.48

37

38

Glasgow

UK

30%

1.51

1.52

5.70

2.67

16.80

9.36

9.13

8.24

4.73

38

39

Bordeaux

France

40%

1.46

1.31

6.94

2.78

13.80

6.45

6.42

10.00

10.00

39

40

Auckland

New Zealand

38%

1.41

0.88

8.51

12.13

23.70

9.27

5.19

6.87

8.92

40

41

Austin

United States

25%

0.70

0.67

5.21

6.07

16.20

8.18

3.10

8.43

7.35

41

42

Toulouse

France

29%

1.46

1.31

4.64

3.13

13.20

7.36

7.03

9.23

7.91

42

43

Philadelphia

United States

23%

0.70

0.67

5.30

17.19

18.70

7.73

3.10

8.43

6.00

43

44

Edinburgh

UK

29%

1.51

1.52

8.09

5.94

13.70

6.18

9.13

8.24

6.17

44

45

Brisbane

Australia

28%

0.90

0.94

4.22

14.72

17.40

8.73

5.81

7.26

8.42

45

46

London

UK

38%

1.51

1.52

9.91

10.44

16.20

8.09

9.13

8.24

6.85

46

47

Wellington

New Zealand

34%

1.41

0.88

7.77

3.82

10.70

9.64

5.19

6.87

8.94

47

48

Vancouver

Canada

39%

0.93

0.77

8.18

5.87

15.00

9.73

5.19

8.83

5.59

48

49

Liverpool

UK

40%

1.51

1.52

8.60

6.51

15.60

6.55

9.13

8.24

8.42

49

50

Boston

United States

28%

0.70

0.67

6.94

16.44

16.80

7.36

3.10

8.43

5.81

50

51

Paris

France

27%

1.46

1.31

9.50

4.99

15.00

4.45

6.42

10.00

2.31

51

52

Chicago

United States

26%

0.70

0.67

9.26

15.16

13.80

6.64

3.10

8.43

4.22

52

53

Tallinn

Estonia

26%

1.25

1.23

5.37

4.18

8.80

9.45

6.85

9.23

4.58

53

54

Budapest

Hungary

22%

1.20

1.19

2.49

1.86

16.80

4.00

4.58

5.10

7.59

54

55

Melbourne

Australia

33%

0.90

0.94

2.98

15.50

17.50

7.82

5.81

7.26

8.78

55

56

San Diego

United States

27%

0.70

0.67

3.56

10.12

11.20

9.00

3.10

8.43

8.13

56

57

Adelaide

Australia

27%

0.90

0.94

1.90

7.08

11.90

8.36

5.81

7.26

9.33

57

58

Lisbon

Portugal

36%

1.57

1.32

7.19

2.09

8.10

9.09

4.50

9.80

4.73

58

59

Manchester

UK

29%

1.51

1.52

9.10

5.89

14.30

1.36

3.01

10.00

7.21

59

60

Tel Aviv

Israel

39%

1.69

1.55

5.63

1.72

21.90

2.64

8.34

6.47

3.68

60

61

Sydney

Australia

39%

0.90

0.94

9.68

26.34

15.60

8.45

5.81

7.26

4.04

61

62

Cape Town

South Africa

35%

0.96

0.96

7.19

1.02

17.50

2.18

1.09

6.87

3.70

62

63

Copenhagen

Denmark

32%

1.61

1.35

5.79

4.41

16.20

4.82

4.67

5.50

9.35

63

64

Kuala Lumpur

Malaysia

43%

0.49

0.47

2.82

1.06

30.50

2.73

1.35

7.84

4.22

64

65

Miami

United States

30%

0.70

0.67

2.85

6.07

19.40

7.55

3.10

8.43

2.76

65

66

Nice

France

38%

1.46

1.31

4.64

4.99

12.40

4.18

6.42

10.00

7.91

66

67

Johannesburg

South Africa

47%

0.96

0.96

7.77

1.93

26.80

1.73

1.09

6.87

4.74

67

68

Riga

Latvia

23%

1.14

1.01

2.57

2.90

18.10

3.55

4.06

3.54

5.28

68

69

Dublin

Ireland

43%

1.44

1.28

4.47

3.19

9.40

8.91

7.99

7.84

6.65

69

70

New York

United States

35%

0.70

0.67

9.42

27.61

11.20

8.55

3.10

8.43

2.58

70

71

Antwerp

Belgium

30%

1.47

1.35

3.48

2.84

10.00

4.64

4.76

8.04

7.48

71

72

Brussels

Belgium

38%

1.47

1.35

2.82

3.36

14.40

5.27

4.76

8.04

7.71

72

73

Athens

Greece

36%

1.64

1.36

6.04

6.61

35.50

3.18

1.96

9.60

3.14

73

74

Santiago de Chile

Chile

43%

1.13

0.73

2.08

2.74

22.40

2.00

2.83

8.24

4.55

74

75

Milan

Italy

27%

1.63

1.47

1.99

6.03

34.90

3.27

4.93

5.70

4.19

75

76

Los Angeles

United States

45%

0.70

0.67

4.22

10.12

20.50

7.27

3.10

8.43

3.68

76

77

Beijing

China

46%

0.95

0.84

1.83

1.50

22.40

1.64

1.96

5.90

6.26

77

78

Shanghai

China

48%

0.95

0.84

2.24

1.64

34.90

1.82

2.31

2.37

7.17

78

79

Rome

Italy

35%

1.63

1.47

3.30

4.87

22.40

4.36

4.93

5.70

3.52

79

80

Buenos Aires

Argentina

42%

1.30

1.14

4.96

2.01

25.60

4.91

2.75

3.16

1.92

80

81

Sofia

Bulgaria

29%

1.11

1.08

2.66

1.18

13.20

2.91

4.41

2.17

3.02

81

82

Hong Kong

China

41%

1.94

1.52

3.30

3.18

39.20

2.45

1.96

5.90

5.09

82

83

Warsaw

Poland

37%

1.15

1.11

3.81

1.16

10.60

3.64

3.97

2.37

4.01

83

84

Moscow

Russia

41%

0.70

0.65

4.96

3.34

18.10

3.73

1.79

1.77

2.12

84

85

Bangkok

Thailand

61%

0.98

0.73

2.91

1.35

21.20

3.00

1.00

7.07

3.54

85

86

St Petersburg

Russia

44%

0.70

0.65

6.04

3.34

17.40

3.73

1.79

1.77

1.00

86

87

Jakarta

Indonesia

58%

0.63

0.68

1.09

0.38

17.50

2.09

2.66

3.93

3.68

87

88

Bucharest

Romania

50%

1.11

1.10

2.31

0.57

16.20

3.91

4.32

1.00

3.99

88

89

Sao Paulo

Brazil

30%

1.18

0.97

3.20

6.21

15.00

3.36

1.44

2.57

4.06

89

90

Rio de Janeiro

Brazil

37%

1.18

0.97

3.56

4.13

12.50

2.55

1.44

2.57

4.51

90

91

Istanbul

Turkey

49%

1.47

1.29

1.56

1.69

11.80

2.27

4.23

6.87

1.49

91

92

Mexico City

Mexico

66%

0.92

0.87

5.46

6.97

17.50

3.09

2.92

6.09

4.62

92

93

Bogota

Colombia

48%

0.75

0.69

1.56

5.22

12.50

2.36

4.93

4.53

1.22

93

94

Ho Chi Minh City

Vietnam

64%

0.79

0.61

1.16

1.10

14.90

1.91

1.26

2.57

5.77

94

95

Bangalore

India

64%

1.12

0.93

1.32

0.86

18.70

1.45

2.40

4.13

1.94

95

96

Mumbai

India

67%

1.12

0.93

6.04

0.95

8.10

1.55

2.40

4.13

3.20

96

97

Ulaanbaatar

Mongolia

65%

0.63

0.68

1.00

2.00

21.80

1.18

1.61

1.20

4.19

97

98

Lagos

Nigeria

60%

0.46

0.65

1.25

0.32

10.70

1.00

1.70

2.76

3.50

98

99

Karachi

Pakistan

59%

0.66

0.74

1.38

0.56

11.20

1.09

2.22

3.54

1.81

99

100

Kolkata

India

69%

1.12

0.93

1.41

0.31

11.20

1.27

2.40

4.13

4.24

100

Methodology

To determine the 50 best and 50 worst cities for driving, we first examined the top 500 cities with the highest number of registered vehicles. Looking then into the cities with the most available traffic data, we decided on this definitive list of 100 cities.

To make a comparable quantification of how good or bad each city is to drive, we made a three-step evaluation of the data. First, we ranked the raw data from highest to lowest value and then we awarded a standard score based on their ranking in the following manner:

A low score indicates poor driving quality for that category, with each increasing number indicating that the city is better to drive in. A score of 1 represents the worst conditions possible and 10 indicates the best. Secondly, all categories were given an overall percentage. To create a comprehensive ranking, the Final Score is a weighted average of each individual category, as follows:

Finally, we standardized the data to have a true final score. Note that for the congestion level category we represent the actual % of congestion and for the price of gasoline and diesel we put the actual price.

The study examined several key factors in order to determine the quality of driving in the 100 cities: congestion level, public transport options, the cost of parking, the cost of petrol, air pollution, the average speed between the city centre and the international airport, road fatalities, road quality and road rage.

For the congestion level score, the data was provided primarily by the TomTom Traffic Index. For the cities not included in the TomTom index, data was provided by the city councils of the respective cities. Any traffic delays or congestion caused by temporary construction work was not taken into account for this study.

The public transport options score affects the quality of driving in a city, because if there are poor public transport alternatives then there is no other option than for people to drive their cars, leading to increased congestion, faster degradation of road quality and increased road rage. A lack of off-road alternatives also means that elderly drivers are forced to continue using their cars when it might no longer be safe, leading to more road accidents. The score was calculated based on the length of the rapid transit system and suburban railway network for each city, with more kilometres of metro rail per capita equating to a higher score. Information on the size of the networks was provided by the system operators.

The parking score was calculated based on the cost of parking for one hour. Information on parking was provided by the official parking authority of the city.

The average speed score was based on the average speed between the city centre and the international airport. The average speed was calculated for three times of the day (morning rush hour, midday and evening rush hour), and then the three scores were averaged for a final score.

The air pollution score was calculated based on data provided by the World Health Organisation’s 2016 air quality in cities database.

The petrol price score was based on information from local stations taken on August 18th 2017.

The World Health Organisation’s status report on road safety 2013 was used to calculate the road traffic injuries score for the cities.

The road quality score was based on the Travel & Tourism Competitiveness Report 2013 produced by the World Economic Forum, where citizens of each country were asked to assess the quality of the roads in their country. This is also a national score and does not account for minor differences between cities.

The road rage score was calculated based on the results of a poll conducted in each of the cities asking over 1000 drivers to rate their perception of road rage and the number of incidents witnessed in the past 12 months.